DBMS > BigObject vs. Ehcache vs. EJDB vs. Lovefield

System Properties Comparison BigObject vs. Ehcache vs. EJDB vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Document store

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

bigobject.io

www.ehcache.org

github.com/Softmotions/ejdb

google.github.io/lovefield

Technical documentation

docs.bigobject.io

www.ehcache.org/documentation

github.com/Softmotions/ejdb/blob/master/README.md

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

BigObject, Inc.

Terracotta Inc, owned by Software AG

Softmotions

Google

Initial release

2015

2009

2012

2014

Current release

3.10.0, March 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available

Open Source

GPLv2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

server-less

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JCache

in-process shared library

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Lua

Triggers

yes

Cache Event Listeners

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

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